About rank-based inverse normal transformation

[hmutanqilong]

Dear Xihao, I have some questions about when I perform rank-based inverse normal transformation for my phenotype before fitting the null model. The phenotype is directly performed to the inverse normal transformation? like using the R package RNOmni. OR I need to perform two steps. The first step is that the null model is fit using the original outcome values. And the second step is using residuals to rank-based inverse Normal transform, and then fit the model again, but it seems not to be rescaled. So, which one is more recommended?

Best, Qilong

[xihaoli]

Hi Qilong,

Thanks for your question. Directly transforming the phenotype using the inverse normal transformation is referred to as D-INT, while transforming the phenotype residuals using the inverse normal transformation is referred to as I-INT, both are valid and illustrated with more details in the RNOmni paper. In the STAAR paper, the inverse normal transformation was applied on the phenotype residuals and we then rescaled the inverse normal transformed residuals to the original scale of the phenotype before fitting the null (mixed) model. More details can be found in the STAAR paper.

Hope this is clear.

Best, Xihao

[hmutanqilong]

Thanks for your explanation. And I found that the package GENESIS can also apply the strategy mentioned in the STAAR paper during fitting the null model. Then I can apply the function genesis2staar_nullmodel to convert for STAAR's class.

obj.model.genesis = fitNullModel(Pheno.df, outcome = 'Pheno', 
                                 covars = c('Age' ,'Age2' ,'Sex' ,'PC1' ,'PC2' ,'PC3' ,'PC4' ,'PC5' ,'PC6' ,'PC7' ,'PC8' ,'PC9' ,'PC10'),
                                 cov.mat = Sparse_GRM, family = "gaussian", AIREML.tol=1e-4,
                                 norm.option = 'all', two.stage = T, rescale = 'residSD', verbose = T)
obj_nullmodel_staar <- genesis2staar_nullmodel(obj.model.genesis)

Would it be all right?

[xihaoli]

Hi Qilong,

Yes, that's correct and it is one of the two recommended strategies to fit a null model in the STAARpipeline tutorial.

Best, Xihao

[hmutanqilong]

Very grateful! Xihao. I think I should solve this problem.